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6. Which of the following is an appropriate interpretation of the number 0.0924982 An increase in profits of $100,000 increases predicted sales by $9,249.80. (b) An increase in sales of $100,000 increases predicted profits by $9,249.80. Sales of $100,000 correspond to predicted profits of $9,249.80. - (d) The ratio of predicted profit to observed profit is, on average, 0.092498. (e) The ratio of predicted profits to observed sales is, on average, 0.092498. profits is the respon se variabe

6. Which of the following is an appropriate interpretation of the number 0.0924982 An increase in profits of $100,000 increases predicted sales by $9,249.80. (b) An increase in sales of $100,000 increases predicted profits by $9,249.80. Sales of $100,000 correspond to predicted profits of $9,249.80. - (d) The ratio of predicted profit to observed profit is, on average, 0.092498. (e) The ratio of predicted profits to observed sales is, on average, 0.092498. profits is the respon se variabe

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Use the following for questions 6-7: A random sample of 40 companies on the Forbes 500 list was selected and the relationship between sales (in hundreds of thousands of dollars) and profits (in hundreds of thousands of dollars) was investigated using regression. A least-squares regression line was fitted to the data using statistical software, with sales as the explanatory variable and profits as the response variable. Here is the output from the software: Dependent variable is Profits R-squared = 66.2% = 466.2 with 40 2 = 38 degrees of freedom Variable Constant Sales Coefficient -176.644 0.092498 s.e. of Coefficient 61.16 0.0106 P-value 0.0050 ≤0.0001
Transcribed Image Text:Use the following for questions 6-7: A random sample of 40 companies on the Forbes 500 list was selected and the relationship between sales (in hundreds of thousands of dollars) and profits (in hundreds of thousands of dollars) was investigated using regression. A least-squares regression line was fitted to the data using statistical software, with sales as the explanatory variable and profits as the response variable. Here is the output from the software: Dependent variable is Profits R-squared = 66.2% = 466.2 with 40 2 = 38 degrees of freedom Variable Constant Sales Coefficient -176.644 0.092498 s.e. of Coefficient 61.16 0.0106 P-value 0.0050 ≤0.0001
6. Which of the following is an appropriate interpretation of the number 0.0924982 An increase in profits of $100,000 increases predicted sales by $9,249.80. b) An increase in sales of $100,000 increases predicted profits by $9,249.80. Sales of $100,000 correspond to predicted profits of $9,249.80. (d) The ratio of predicted profit to observed profit is, on average, 0.092498. (e) The ratio of predicted profits to observed sales is, on average, 0.092498. 7 ≤0.0001 Which of the follo profits is the response variabe clogs
Transcribed Image Text:6. Which of the following is an appropriate interpretation of the number 0.0924982 An increase in profits of $100,000 increases predicted sales by $9,249.80. b) An increase in sales of $100,000 increases predicted profits by $9,249.80. Sales of $100,000 correspond to predicted profits of $9,249.80. (d) The ratio of predicted profit to observed profit is, on average, 0.092498. (e) The ratio of predicted profits to observed sales is, on average, 0.092498. 7 ≤0.0001 Which of the follo profits is the response variabe clogs
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